A new proactive feature selection model based on the enhanced optimization algorithms to detect DRDoS attacks

Cyberattacks have grown steadily over the last few years. The distributed reflection denial of service (DRDoS) attack has been rising, a new variant of distributed denial of service (DDoS) attack. DRDoS attacks are more difficult to mitigate due to the dynamics and the attack strategy of this type of attack. The number of features influences the performance of the intrusion detection system by investigating the behavior of traffic. Therefore, the feature selection model improves the accuracy of the detection mechanism also reduces the time of detection by reducing the number of features. The proposed model aims to detect DRDoS attacks based on the feature selection model, and this model is called a proactive feature selection model proactive feature selection (PFS). This model uses a nature-inspired optimization algorithm for the feature subset selection. Three machine learning algorithms, i.e., k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM), were evaluated as the potential classifier for evaluating the selected features. We have used the CICDDoS2019 dataset for evaluation purposes. The performance of each classifier is compared to previous models. The results indicate that the suggested model works better than the current approaches providing a higher detection rate (DR), a low false-positive rate (FPR), <span>and increased accuracy detection (DA).</span> The PFS model shows better accuracy to detect DRDoS attacks with 89.59%.

Individual Disturbance and Attraction Repulsion Strategy Enhanced Seagull Optimization for Engineering Design

The seagull optimization algorithm (SOA) is a novel swarm intelligence algorithm proposed in recent years. The algorithm has some defects in the search process. To overcome the problem of poor convergence accuracy and easy to fall into local optimality of seagull optimization algorithm, this paper proposed a new variant SOA based on individual disturbance (ID) and attraction-repulsion (AR) strategy, called IDARSOA, which employed ID to enhance the ability to jump out of local optimum and adopted AR to increase the diversity of population and make the exploration of solution space more efficient. The effectiveness of the IDARSOA has been verified using representative comprehensive benchmark functions and six practical engineering optimization problems. The experimental results show that the proposed IDARSOA has the advantages of better convergence accuracy and a strong optimization ability than the original SOA.

Detection of a New Variant in Outbreak of Bovine Ephemeral Fever in Turkey, 2020

Background: In this study, partial nucleotide sequence analysis of the G gene was performed for the molecular characterization of the virus that caused the bovine ephemeral fever virus (BEFV) epidemic in Turkey in 2020. Phylogenetic analysis of these nucleotide sequences was performed with the virus nucleotide sequences of the epidemics seen in 2008 and 2012. These sequences were announced in GenBank. Phylogenetic analysis of these nucleotide sequences was performed with the virus nucleotide sequences of the epidemics seen in 2008 and 2012. Methods: The study was conducted in dairy cattle holdings located in Diyarbakır Sur, Çınar and Dicle regions in South-eastern Turkey in August-November 2020. The number of animals in the holdings consisted of 750 (n=750), 150 (n=150) and 200 (n=200) cattle, respectively. Result: Severe respiratory symptoms and high mortality in the affected animals were notable symptoms. As a result of the phylogenetic analysis, it was determined that the virus that caused the epidemic in Turkey in 2020 was formed by a new variant in the Turkey-2 group, which was similar to the Indian isolates, unlike the Turkey-1 group, which was close to the Middle East variants in 2008 and 2012 isolates.

Genetic Characterization and Variation of African Swine Fever Virus China/GD/2019 Strain in Domestic Pigs

African swine fever (ASF) was first introduced into Northern China in 2018 and has spread through China since then. Here, we extracted the viral DNA from the blood samples from an ASF outbreak farm in Guangdong province, China and sequenced the whole genome. We assembled the full length genomic sequence of this strain, named China/GD/2019. The whole genome was 188,642 bp long (terminal inverted repeats and loops were not sequenced), encoding 175 open reading frames (ORF). The China/GD/2019 strain belonged to p72 genotype II and p54 genotype IIa. Phylogenetic analysis relationships based on single nucleotide polymorphisms (SNPs) also demonstrated that it grouped into genotype II. A certain number of ORFs mainly belonging to multigene families (MGFs) were absent in the China/GD/2019 strain in comparison to the China/ASFV/SY-18 strain. A deletion of approximately 1 kb was found in the China/GD/2019 genome which was located at the EP153R and EP402R genes in comparison to the China/2018/AnhuiXCGQ strain. We revealed a synonymous mutation site at gene F317L and a non-synonymous mutation site at gene MGF_360-6L in China/GD/2019 comparing to three known Chinese strains. Pair-wise comparison revealed 165 SNP sites in MGF_360-1L between Estonia 2014 and the China/GD/2019 strain. Comparing to China/GD/2019, we revealed a base deletion located at gene D1133L in China/Pig/HLJ/2018 and China/DB/LN/2018, which results in a frameshift mutation to alter the encoding protein. Our findings indicate that China/GD/2019 is a new variant with certain deletions and mutations. This study deepens our understanding of the genomic diversity and genetic variation of ASFV.

New mutation of the TP53 gene associated with the hereditary breast cancer in a young Tuvinian woman

Background. The identification of the ethnospecific mutations associated with hereditary breast cancer remains challenging. Next generation sequencing (Ngs) technology fully enables the compilation of germline variants associated with the risk for inherited diseases. Despite the success of the Ngs, up to 20 % of molecular tests report genetic variant of unknown significance (Vus) or novel variants that have never been previously described and their clinical significances are unknown. To obtain extended information about the variants of the unknown significance, it is necessary to use an alternative approach for the analysis of the Ngs data. To obtain extended characteristic about the unknown significance variants, it is necessary to search for additional tools for the analysis of the Ngs data. Material and methods. We reclassified the mutation of the unknown significance using the activedrivedb database that assessed the effect of mutations on sites of post-translational modifications, and the proteinpaint tool that complemented the existing cancer genome portals and provided a comprehensive and intuitive view of cancer genomic data. Results. In this study, we report a 44-year-old tuvinian woman with a family history of breast cancer. Based on the Ngs data, mutational analysis revealed the presence of the lrg_321t1: c.80c>t heterozygous variant in exon 2, which led to the proline to leucine change at codon 27 of the protein. In the dbpubmed database, this mutation was determined as unknown significance due to data limitation. According to the data of the activedriverdb tool, this mutation is located distally at the site of post-translational protein modification, which is responsible for binding to kinases that regulate genes of the cell cycle, etc. (atm, chek2, cdk, mapk). In accordance with proteinpaint tool, the lrg_321t1: c.80c>t mutation is located in functionally specialized transactivation domains and codon of the tp53 gene, where the pathogenic mutation associated with li-Fraumeni syndrome has been earlier described. Conclusion. This report is the first to describe a new variant in the tp53 gene (rs1555526933), which is likely to be associated with hereditary cancer-predisposing syndrome, including li-Fraumeni syndrome, in a tuvinian Bc patient with young-onset and familial Bc.

The SARS-CoV-2 Omicron (B.1.1.529) variant exhibits altered pathogenicity, transmissibility, and fitness in the golden Syrian hamster model

The newly emerging SARS-CoV-2 Omicron (B.1.1.529) variant first identified in South Africa in November 2021 is characterized by an unusual number of amino acid mutations in its spike that renders existing vaccines and therapeutic monoclonal antibodies dramatically less effective. The in vivo pathogenicity, transmissibility, and fitness of this new Variant of Concerns are unknown. We investigated these virological attributes of the Omicron variant in comparison with those of the currently dominant Delta (B.1.617.2) variant in the golden Syrian hamster COVID-19 model. Omicron-infected hamsters developed significantly less body weight losses, clinical scores, respiratory tract viral burdens, cytokine/chemokine dysregulation, and tissue damages than Delta-infected hamsters. The Omicron and Delta variant were both highly transmissible (100% vs 100%) via contact transmission. Importantly, the Omicron variant consistently demonstrated about 10-20% higher transmissibility than the already-highly transmissible Delta variant in repeated non-contact transmission studies (overall: 30/36 vs 24/36, 83.3% vs 66.7%). The Delta variant displayed higher fitness advantage than the Omicron variant without selection pressure in both in vitro and in vivo competition models. However, this scenario drastically changed once immune selection pressure with neutralizing antibodies active against the Delta variant but poorly active against the Omicron variant were introduced, with the Omicron variant significantly outcompeting the Delta variant. Taken together, our findings demonstrated that while the Omicron variant is less pathogenic than the Delta variant, it is highly transmissible and can outcompete the Delta variant under immune selection pressure. Next-generation vaccines and antivirals effective against this new VOC are urgently needed.

A novel subgenotype C6 Enterovirus A71 originating from the recombination between subgenotypes C4 and C2 strains in mainland China

Recombination plays important roles in the genetic diversity and evolution of Enterovirus A71 (EV-A71). The phylogenetics of EV-A71 in mainland China found that one strain DL71 formed a new subgenotype C6 with unknown origin. This study investigated the detailed genetic characteristics of the new variant. DL71 formed a distinct cluster within genotype C based on the genome and individual genes (5′UTR, VP4, VP1, 2A, 2B, 2C, 3D, and 3′UTR). The average genetic distances of the genome and individual genes (VP3, 2A, 2B, 2C, 3A, 3C, and 3D) between DL71 and reference strains were greater than 0.1. Nine recombination events involving smaller fragments along DL71 genome were detected. The strains Fuyang-0805a (C4) and Tainan/5746/98 (C2) were identified as the parental strains of DL71. In the non-recombination regions, DL71 had higher identities with Fuyang-0805a than Tainan/5746/98, and located in the cluster with C4 strains. However, in the recombination regions, DL71 had higher identities with Tainan/5746/98 than Fuyang-0805a, and located in the cluster with C2 strains. Thus, DL71 was a novel multiple inter-subgenotype recombinant derived from the dominant subgenotype C4 and the sporadic subgenotype C2 strains. Monitoring the emergence of new variants by the whole-genome sequencing remains essential for preventing disease outbreaks and developing new vaccines.

Discrete Approximate Solution of Differential Inclusion with Normal Cone and Prox-Regular Set.

Our aim is to calculate the discrete approximate solution of di⁄erential inclusion with normal cone and prox-regular set, the question is how to calculate this solution? We use the discrete approximation property of a new variant of nonconvex sweeping processes involving normal cone and a nite element method. Knowing that The majority of mathematicians have proved only the existence and uniqueness of the solution for this type of inclusions, like: Mordukhovich, Thibault, Aubin, Messaoud, ...etc.

Optimizing pre-clerkship medical education at the University of Ottawa

COVID-19 has brought forth unprecedented changes in the delivery of medical education. With concerns rising over a new variant and an upheaval in vaccine distribution, institutions have had to re-strategize and, in many cases, implement provisional shutdowns to contain the spread of SARS-CoV-2. For medical schools, providing an optimal balance between in-person training and virtual learning has been challenging. At the University of Ottawa Faculty of Medicine, key components of the undergraduate medical education, including in-class lectures, interactive practical sessions, and clinical placements, have been affected by the pandemic. In this paper, we highlight barriers to an optimal learning experience among pre-clerkship students at the University of Ottawa and propose ways in which this can be overcome.